What is Data as a Service (DaaS)?

How to combine Data to provide Service? How to leverage your own Data to extract profits?

Data as a Service (DaaS) is a data management strategy that aims to leverage data as a business asset for greater business agility. It is part of the “as a service” offerings that have become increasingly popular since the expansion of the internet in the 1990s, which began with the introduction of Software as a Service (SaaS). Similar to other “as a service” models, DaaS provides a way to manage the massive amounts of data organizations generate every day and deliver that valuable information across the business for data-driven decision making.

Essentially, DaaS provides a way for businesses to tap into their increasingly vast and complex data sources to serve up the most important insights to users. This democratization of data is critical for any business wanting to turn data into real value. It represents a huge opportunity to monetize an organization’s data and gain a competitive advantage with a more data-centric approach to business operations and processes.

What are the benefits of Data as a Service?

The potential impact of Data as a Service (DaaS) is huge. And not just in terms of revenue, DaaS can benefit the entire organization and its customers when successfully leveraged. The following are some major benefits that DaaS may bring businesses over time:

• Monetizing Data: Having enough data is no longer a major issue for most companies today. It’s organizing and operationalizing that data that presents the biggest challenge in today’s market. While many CEOs have invested heavily in data monetization initiatives, very few have successfully leveraged the full value of their data. DaaS could be a key way to reach that goal. Increasing data accessibility can.
• Lower costs: Capitalizing on all of a business’s wide range of data sources, uncovering insights, and delivering those insights to different areas of the business to act smarter can greatly decrease spending time and money on the wrong decisions. DaaS means less following your gut and more data-driven decisions, wasting less of your resources on pointless, ill-informed efforts. Furthermore, DaaS can help companies develop personalized customer experiences by using predictive analytics to understand consumer behaviors and patterns, better serve customers, and gain their loyalty.
• Faster Paths to Innovation: Think of DaaS as opening the doors to growth. With data at the center of a business, growth happens quickly. That is because data-informed strategies allow for more innovation with less risk. When trustworthy data is provisioned to different departments and teams that need it, ideas based on that data have a better chance of gaining buy-in from other areas of the business and ultimately succeeding once put into practice. Ideas can take flight faster with access to data that informs new initiatives and spurs on growth.
• More Agile Decision Making: Data as a Service (DaaS) represents a great opportunity for many businesses to treat data as an important business asset for more strategic decision making and effective data management. It can combine both internal and external data sources, such as customer, partner, and open data sources, for a comprehensive view of the business. DaaS can also be used to quickly deliver data for purpose-built analytics with end-to-end APIs serving specific business use cases. DaaS can help support self-service data access, simplifying business user data access with an intuitive, self-service directory. This can reduce the time spent searching for data and increase the time spent analyzing and acting on the data.
• Data-Driven Culture: Breaking down data silos and getting teams the data they need is a huge challenge for businesses today. DaaS grants businesses the ability to deliver integrated data from a growing list of data sources, fostering a data-driven culture and democratizing the use of data in everyday processes. DaaS also helps companies manage today’s rising tide of data and growing data complexity through reusable datasets for broad data consumption. These reusable data assets can promote both inter-enterprise and intra-enterprise sharing, establishing a central understanding of the business. By opening up access to critical data resources, DaaS can help organizations infuse data into their business practices.
• Lower Risks: DaaS can help to remove some of the personal biases in decision making that often put companies at risk. Businesses powered by guesswork often fail. Businesses that rely on a DaaS provider are empowered by data to take the right actions and win. With DaaS, companies can leverage data virtualization and other technologies to access, combine, transform, and deliver data via reusable data services, optimizing query performance and ensuring data security and governance. In this way, DaaS helps lower risks associated with conflicting or incomplete data views or poor data quality.

Challenges to Data as a Service

While many business use cases could potentially benefit from DaaS, there are several challenges that organizations should be aware of before making an investment.

The first challenge organizations may face when applying DaaS is the complexity of data. DaaS deals with all the data across the entire organization, not just one area or problem to solve, meaning the roadmap for such a project must be comprehensive and may take time to carry out correctly. This is especially true for large corporations overwhelmed by unstructured datasets.

On the same thread, DaaS can be challenging because it often requires a company-wide strategy and may require direction from the C-Suite. In fact, it is often part of a larger endeavor to make an organization more data driven, break down data silos, and democratize data access.

Finally given the increasingly sophisticated nature of data security threats today, it is essential that security be a top concern for any DaaS implementation. That means ensuring that the appropriate data governance, security, privacy, and other data quality controls are applied to new DaaS components. All data assets should also be well-documented and locatable.